Postoperative communicating hydrocephalus has been recognized in patients with brain tumors. The associated changes in ventricle volume can be difficult to identify, particularly over short time intervals. Potentially, accurate ventricle volume estimates could provide for a better understanding of communicating hydrocephalus, and lead to more confident diagnoses. Our method evaluates ventricle size from serial brain MRI examinations, we (1) combined serial images to increase SNR (2) segmented this image to generate a ventricle template using fats marching methods and geodesic active contours, and (3) propagate the segmentation using deformable registration of the original MRI datasets. By applying this deformation to the ventricle template, serial volume estimates were obtained in a robust manner.